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<p>Optimizing pre-treatment in reverse osmosis (RO) demineralization systems is crucial for ensuring optimum water quality and prolonging membrane life by limiting rapid fouling. In this study, the treatment of water from the Aït Massoud dam, which supplies Maroc Central's reverse osmosis (RO) demineralization plant, was optimized using a Box-Behnken design. Three factors were studied: aluminum sulfate dose (10, 40 and 70 mg/L), polyelectrolyte dose (0.1, 0.2 and 0.3 mg/L) and recirculated sludge volume (5, 50 and 95 mL), to assess their impact on turbidity and oxidizable matter (OM) removal. The factors of recirculation sludge volume and aluminum sulfate dose affected the removal of turbidity and OM to the greatest extent possible. The optimum doses found for the removal of turbidity and OM were 46 mg/L aluminum sulfate, 0.22 mg/L polyelectrolyte, and 52 mL of sludge per liter of water. With these optimum doses, model results predicted 100% removal of turbidity and 72% removal of OM. These optimum doses were subsequently applied at full scale in the Maroc Central treatment plant. The findings indicated efficiency, for turbidity removal ranged from 94.12% to 98.49% and OM removal from 69.23% to 72.73%. The results were in close agreement with the model predicted values thus providing further assurance of the viability of this model for practical purposes under real operating conditions. Besides enhancing water treatment performance, the process resulted in a 38% reduction in sludge generation, 15% reduction in coagulant application, and 11.5% reduction in energy requirements while increasing membrane cleaning cycles by 43%. Such improvements generated annual savings of about €60,150, strengthening the case for economic and environmental sustainability. However, the findings are site-specific and require validation under varying conditions and extended operation to assess long-term performance and reliability.</p>

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Sustainable Optimization of Reverse Osmosis Pretreatment of Brackish Water Using Coagulation-Flocculation and Sludge Recirculation: A Box-Behnken Approach

  • 期刊论文

  • 发表日期：

    2025年10月4日

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  • Radouane El Amri,
  • Rajaa Zahnoune,
  • Otmane Boudouch,
  • Cherki Lahlou,
  • Aziz Hasib,
  • Noureddine Kamil,
  • Reda Elkacmi

摘要

Optimizing pre-treatment in reverse osmosis (RO) demineralization systems is crucial for ensuring optimum water quality and prolonging membrane life by limiting rapid fouling. In this study, the treatment of water from the Aït Massoud dam, which supplies Maroc Central's reverse osmosis (RO) demineralization plant, was optimized using a Box-Behnken design. Three factors were studied: aluminum sulfate dose (10, 40 and 70 mg/L), polyelectrolyte dose (0.1, 0.2 and 0.3 mg/L) and recirculated sludge volume (5, 50 and 95 mL), to assess their impact on turbidity and oxidizable matter (OM) removal. The factors of recirculation sludge volume and aluminum sulfate dose affected the removal of turbidity and OM to the greatest extent possible. The optimum doses found for the removal of turbidity and OM were 46 mg/L aluminum sulfate, 0.22 mg/L polyelectrolyte, and 52 mL of sludge per liter of water. With these optimum doses, model results predicted 100% removal of turbidity and 72% removal of OM. These optimum doses were subsequently applied at full scale in the Maroc Central treatment plant. The findings indicated efficiency, for turbidity removal ranged from 94.12% to 98.49% and OM removal from 69.23% to 72.73%. The results were in close agreement with the model predicted values thus providing further assurance of the viability of this model for practical purposes under real operating conditions. Besides enhancing water treatment performance, the process resulted in a 38% reduction in sludge generation, 15% reduction in coagulant application, and 11.5% reduction in energy requirements while increasing membrane cleaning cycles by 43%. Such improvements generated annual savings of about €60,150, strengthening the case for economic and environmental sustainability. However, the findings are site-specific and require validation under varying conditions and extended operation to assess long-term performance and reliability.